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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Dependence of CCN closure relationship with organic fraction from two airborne field campaigns over mid-latitude land and ocean

This study investigates the relationship between measured and calculated cloud condensation nuclei (CCN) number concentration and its dependence with organic fraction utilizing aircraft observations from The Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA, 2017–2018) and The Holistic Interactions of Shallow Clouds, Aerosols, and Land Ecosystems (HI-SCALE, 2016) campaigns, which represent midlatitude marine and continental environments, respectively. For the ACE-ENA marine region, aerosol and CCN concentrations were significantly higher in summer than in winter, whereas at continental site for HI-SCALE, aerosol and CCN concentrations showed no pronounced differences between spring and autumn. Using aerosol chemical composition and number size distribution data, CCN concentrations at various supersaturations are calculated based on Köhler theory and then compared with observations from CCN counter. The results show that CCN closure performs well at both sites with a slight overestimation, with mean closure ratio (CR) of 1.13 and 1.17, respectively. Further investigation reveals that CR at lower supersaturation perform better than that at higher supersaturation. The dependence of CR on organic mass fraction (MForg) varies by environment: for marine aerosols, CR decreases with increasing organic fraction at lower supersaturations, whereas continental aerosols exhibit a consistent overestimation, with CR decreasing as organic fraction increases at higher supersaturations. This study provides key insights into CCN characteristics over midlatitude marine and continental environments, emphasizing the necessity of incorporating size-resolved chemical composition and mixing states into future model parameterizations, and contributing to a better understanding of aerosol–cloud interactions.

ACE-ENA field campaign↗
DOE OSTI2012

Effect of Terrestrial and Marine Organic Aerosol on Regional and Global Climate: Model Development, Application, and Verification with Satellite Data

In this DOE project the improvements to parameterization of marine primary organic matter (POM) emissions, hygroscopic properties of marine POM, marine isoprene derived secondary organic aerosol (SOA) emissions, surfactant effects, new cloud droplet activation parameterization have been implemented into Community Atmosphere Model (CAM 5.0), with a seven mode aerosol module from the Pacific Northwest National Laboratory (PNNL)'s Modal Aerosol Model (MAM7). The effects of marine aerosols derived from sea spray and ocean emitted biogenic volatile organic compounds (BVOCs) on microphysical properties of clouds were explored by conducting 10 year CAM5.0-MAM7 model simulations at a grid resolution 1.9° by 2.5° with 30 vertical layers. Model-predicted relationship between ocean physical and biological systems and the abundance of CCN in remote marine atmosphere was compared to data from the A-Train satellites (MODIS, CALIPSO, AMSR-E). Model simulations show that on average, primary and secondary organic aerosol emissions from the ocean can yield up to 20% increase in Cloud Condensation Nuclei (CCN) at 0.2% Supersaturation, and up to 5% increases in droplet number concentration of global maritime shallow clouds. Marine organics were treated as internally or externally mixed with sea salt. Changes associated with cloud properties reduced (absolute value) the model-predicted short wave cloud forcing from -1.35 Wm -2 to -0.25 Wm -2 . By using different emission scenarios, and droplet activation parameterizations, this study suggests that addition of marine primary aerosols and biologically generated reactive gases makes an important difference in radiative forcing assessments. All baseline and sensitivity simulations for 2001 and 2050 using global-through-urban WRF/Chem (GU-WRF) were completed. The main objective of these simulations was to evaluate the capability of GU-WRF for an accurate representation of the global atmosphere by exploring the most accurate configuration of physics options in GWRF for global scale modeling in 2001 at a horizontal grid resolution of 1° x 1°. GU-WRF model output was evaluated using observational datasets from a variety of sources including surface based observations (NCDC and BSRN), model reanalysis (NCEP/ NCAR Reanalysis and CMAP), and remotely-sensed data (TRMM) to evaluate the ability of GU-WRF to simulate atmospheric variables at the surface as well as aloft. Explicit treatment of nanoparticles produced from new particle formation in GU-WRF/Chem-MADRID was achieved by expanding particle size sections from 8 to 12 to cover particles with the size range of 1.16 nm to 11.6m. Simulations with two different nucleation parameterizations were conducted for August 2002 over a global domain at a 4º by 5º horizontal resolution. The results are evaluated against field measurement data from the 2002 Aerosol Nucleation and Real Time Characterization Experiment (ANARChE) in Atlanta, Georgia, as well as satellite and reanalysis data. We have also explored the relationship between clean marine aerosol optical properties and ocean surface wind speed using remotely sensed data from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the CALIPSO satellite and the Advanced Microwave Scanning Radiometer (AMSR-E) on board the AQUA satellite. Detailed data analyses were carried out over 15 regions selected to be representative of different areas of the global ocean for the time period from June 2006 to April 2011. We show that for very low (less than 4 m s -1 ) and very high (more than 12 m s -1 ) wind speed conditions the mean CALIPSO-derived aerosol optical depth (AOD) has little dependency on the surface wind speed. For an intermediate (between 4 and 12 m s -1 ) marine AOD was linearly correlated with the surface wind speed values, with a slope of 0.0062 s m -1 . Results of our study suggest that considerable improvements to both optical properties of marine aerosols and their production mechanisms can be achieved by discriminating clean marine aerosols (or sea salt particles) from all other types of aerosols present over the ocean.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Automated Tracking of Shallow Cu Growth Rates on Geostationary Imagery and Linkages to Cloud Organization

Shallow moist convection is ubiquitous throughout the tropics and represents a key player in boundary layer processes. Common tropical cloud features, such as convective rolls and cold pool fronts, form and persist for different periods within environments that support such development. Determining differences in lifecycle amongst these features in varying environments requires viewing their evolution from initiation to decay. Geostationary satellites provide a means to follow the clouds with enhanced spatiotemporal sampling from space. We apply a cloud-tracking tool to study lifecycle properties of shallow cumulus sampled during the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex) field campaign of 2019. The mission conducted airborne and shipborne operations over the West Pacific Ocean, in tandem with Rapid Scan imagery from the Advanced Himawari Imager (AHI) on the Japan Meteorological Agency’s (JMA) Himawari-8 satellite. Shallow cumulus was segmented on AHI 0.5-km visible reflectance and tracked during the daylit hours of several research flights that exhibited ideal atmospheric conditions for tracking. The resulting cloud tracks were collected according to regions containing airborne sampling of individual clouds at various stages of their lifecycles, yielding ensembles of tracks in separate environments. We present an analysis on lifecycle properties extracted from the cloud-track ensembles and their potential connections to cloud organizations observed throughout CAMP2Ex. Each ensemble is evaluated by calculating cloud-layer growth rates and comparing to spatial parameters, including track-achieved area and cloud-top height. The apparent clustering of growth rates for specific ensembles is then compared against overall cloud organizations, such as isolated congestus and cold pool fronts, that are observed with the airborne data. Finally, we consider how such differences in cloud growth appear in the airborne radar observations of intercepted cloud tracks.

Cloud Tracking↗
NASA NTRS2024

Classifying Microwave Radiometer Observations Over the Netherlands Into Dry, Shallow-, and Non-Shallow Precipitation Using A Random Forest Model

Spaceborne microwave radiometers represent an important component of the Global Precipitation Measurement (GPM) mission due to their frequent sampling of rain systems. Microwave radiometers measure microwave radiation (brightness temperatures, Tb), which can be converted into precipitation estimates with appropriate assumptions. However, detecting shallow precipitation systems using space-borne radiometers is challenging, especially over land, as their weak signals are hard to differentiate from those associated with dry conditions. This study uses a random forest model (RF) to classify microwave radiometer observations as dry, shallow, or nonshallow over the Netherlands - a region with varying surface conditions and frequent occurrence of shallow precipitation. The RF is trained on five years of data (2016-2020) and tested with two independent years (2015, 2021). The observations are classified using ground-based weather radar echo top heights. Various RF models are assessed, such as using only GPM’s Microwave Imager (GMI) Tb values as input features or including spatially aligned ERA-5 2-meter temperature and freezing level reanalysis and/or Dual Precipitation Radar (DPR) observations. Independent of the input features, the model performs best in summer and worst in winter. The model classifies observations from high-frequency channels (≥85 GHz) with lower Tb-values as non-shallow, higher values as dry, and those in between as shallow. Misclassified footprints exhibit radiometric characteristics corresponding to their assigned class. Case studies reveal dry observations misclassified as shallow are associated with lower Tb-values, likely resulting from the presence of ice particles in non-precipitating clouds. Shallow footprints misclassified as dry are likely related to the absence of ice particles.

Linda Bogerd↗
NASA NTRSDate not supplied

Simultaneous lidar profiling of water vapor, aerosol, and wind over the eastern Pacific and implications for observational challenges on clouds, circulation, and climate sensitivity

Moist convective processes and related circulations are key components of the Earth’s climate system. Improving our understanding of moisture and cloud processes over oceans is especially challenging due to observational limitations, but also important due to the large radiative effects of cloud over ocean as well as the ties to local and global-scale circulations. A unique dataset for addressing these topics was collected over 5 flights with the NASA HALO (water vapor DIAL and aerosol HSRL) and DAWN (Doppler wind) lidar systems onboard the NASA DC-8 aircraft during the spring 2019 ADM-Aeolus Cal/Val test flight campaign. High-resolution water vapor, aerosol/cloud, and wind profiles were simultaneously collected and complimented with in situ high-resolution dropsonde measurements of temperature, relative humidity, and wind profiles. Airborne lidar measurements of these key variables captured both large-scale spatial variability across different cloud and atmospheric conditions as well as finer features, providing insight into processes from large-scale circulations down to aerosol/cloud interactions. The 5 flights spanned the northeast Pacific and southwest U.S. from 6 N to 52 N and 112 W to 157 W and captured several features of interest including moist layers from the ascending region of the Hadley circulation, very dry layers above midlatitude marine stratocumulus and cloud-free planetary boundary layers, and cloud top height and spatial variability. High covariance of aerosol and water vapor in the free troposphere was also observed for the first time. Preliminary analysis of these data sets will be presented as they apply to clouds and circulations, supplemented by model reanalysis to inform how regional water vapor structure and large-scale motion may contribute to observed shallow cloud formations and other meteorological processes that underpin our current understanding of how these state variables couple to impact the Earth’s weather and climate systems. The potential of complementary measurements in future field campaigns will also be mentioned.

Brian James Carroll↗
DOE OSTI2015

Continuous Evaluation of Fast Processes in Climate Models Using Arm Measurements

Under the support of this grant, we investigated the fast process of interaction of clouds, shallow convection, and boundary layer turbulence and their parameterizations. Main accomplishments involve two things. One is the understanding of the physical mechanisms of low cloud feedbacks; the second is the development and evaluation of convection and cloud parameterizations in climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Effects of cloud condensation nuclei and ice nucleating particles on precipitation processes and supercooled liquid in mixed-phase orographic clouds

How orographic mixed-phase clouds respond to the change in cloud condensation nuclei (CCN) and ice nucleating particles (INPs) are highly uncertain. The main snow production mechanism in warm and cold mixed-phase orographic clouds (referred to as WMOCs and CMOCs, respectively, distinguished here as those having cloud tops warmer and colder than −20 °C) could be very different. We quantify the CCN and INP impacts on supercooled water content, cloud phases, and precipitation for a WMOC case and a CMOC case, with sensitivity tests using the same CCN and INP concentrations between the WMOC and CMOC cases. It was found that deposition plays a more important role than riming for forming snow in the CMOC case, while the role of riming is dominant in the WMOC case. As expected, adding CCN suppresses precipitation, especially in WMOCs and low INPs. However, this reverses strongly for CCN of 1000 cm −3 and larger. We found a new mechanism through which CCN can invigorate mixed-phase clouds over the Sierra Nevada and drastically intensify snow precipitation when CCN concentrations are high (1000 cm −3 or higher). In this situation, more widespread shallow clouds with a greater amount of cloud water form in the Central Valley and foothills west of the mountain range. The increased latent heat release associated with the formation of these clouds strengthens the local transport of moisture to the windward slope, invigorating mixed-phase clouds over the mountains, and thereby producing higher amounts of snow precipitation. Under all CCN conditions, increasing the INPs leads to decreased riming and mixed-phase fraction in the CMOC as a result of liquid-limited conditions, but has the opposite effects in the WMOC as a result of ice-limited conditions. However, precipitation in both cases is increased by increasing INPs due to an increase in deposition for the CMOC but enhanced riming and deposition in the WMOC. Increasing the INPs dramatically reduces supercooled water content and increases the cloud glaciation temperature, while increasing CCN has the opposite effect with much smaller significance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Collaborative Project: Contributions of organic compounds to the growth of freshly nucleated atmospheric nanoparticles. Final Report

New-particle formation (NPF) is a significant source of aerosol particles into the atmosphere. However, these particles are initially too small to have climatic importance and must grow, primarily through net uptake of low-volatility species and more volatile gases that react in particles to form stable compounds, from diameters of ~1 nm to 30–100 nm in order to potentially impact climate. At the present time there are uncertainties in the physical and chemical processes associated with the growth of these freshly formed particles that lead to uncertainties in model predictions of aerosol-climate interactions. In this project, we used a combination of field, laboratory, and modelling studies to understand the processes leading to nanoparticle growth and evaluated and improved growth in global aerosol models. During this period this research team has either participated in, or analyzed observations from, four DOE-funded campaigns: the 2013 New Particle Formation Study (NPFS) at the ARM Southern Great Plains (SGP) site; the 2013 Biogenic Aerosols – Effects on Clouds and Climate campaign (BAECC) in Hyytiala, Finland; Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) in central Amazonia, Brazil; and, most recently, the 2016 Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) campaign at the SGP site. In addition, the research team explored nanoparticle growth mechanisms in laboratory experiments at the National Center for Atmospheric Research, University of California, Irvine, and the CLOUD chamber in Geneva, Switzerland. Modeling efforts resulted in a process-level model that incorporated both salt formation and the uptake of low-volatility organic compounds, which was able to connect measurements of gas and nanoparticle phase compounds observed during NPFS. In total, the results of this work have been described in 32 peer-reviewed publications and 34 invited or conference presentations.

58 GEOSCIENCES↗
DOE OSTI2018

Final Report: Collaborative Project: Contributions of organic compounds to the growth of freshly nucleated atmospheric nanoparticles

New-particle formation (NPF) is a significant source of aerosol particles into the atmosphere. However, these particles are initially too small to have climatic importance and must grow, primarily through net uptake of low-volatility species and more volatile gases that react in particles to form stable compounds, from diameters of ~1 nm to 30–100 nm in order to potentially impact climate. At the present time there are uncertainties in the physical and chemical processes associated with the growth of these freshly formed particles that lead to uncertainties in model predictions of aerosol-climate interactions. In this project, we used a combination of field, laboratory, and modelling studies to understand the processes leading to nanoparticle growth and evaluated and improved growth in global aerosol models. During this period this research team has either participated in, or analyzed observations from, four DOE-funded campaigns: the 2013 New Particle Formation Study (NPFS) at the ARM Southern Great Plains (SGP) site; the 2013 Biogenic Aerosols – Effects on Clouds and Climate campaign (BAECC) in Hyytiala, Finland; Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) in central Amazonia, Brazil; and, most recently, the 2016 Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) campaign at the SGP site. In addition, the research team explored nanoparticle growth mechanisms in laboratory experiments at the National Center for Atmospheric Research, University of California, Irvine, and the CLOUD chamber in Geneva, Switzerland. Modeling efforts resulted in a process-level model that incorporated both salt formation and the uptake of low-volatility organic compounds, which was able to connect measurements of gas and nanoparticle phase compounds observed during NPFS. In total, the results of this work have been described in 32 peer-reviewed publications and 34 invited or conference presentations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Examining the vertical heterogeneity of aerosols over the Southern Great Plains

Abstract. Atmospheric aerosols affect the global energy budget by scattering and absorbing sunlight (direct effects) and by changing the microphysical structure, lifetime, and coverage of clouds (indirect effects). Both aerosol direct and indirect effects are affected by the vertical distribution of aerosols in the atmosphere, which is further influenced by a range of processes, such as aerosol dynamics, long-range transport, and entrainment. However, many observations of these processes are based on ground measurements, limiting our ability to understand the vertical distribution of aerosols and simulate their impact on clouds and climate. In this work, we examined the vertical heterogeneity of aerosols over the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) using data collected from the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) campaign. The vertical profiles of meteorological and aerosol physiochemical properties up to 2500 m above are examined based on the 38 flights conducted during the HI-SCALE campaign. The aerosol properties over the SGP show strong vertical heterogeneity and seasonal variabilities. The aerosol concentrations at the surface are the highest due to strong emissions at ground level. In general, the mode diameter of aerosols during summer (∼ 100 nm) is larger than that during spring (∼ 30 nm), a result of enhanced condensational growth due to enriched volatile organic compounds in summer. The concentration of aerosols below 30 nm in the boundary layer (BL) (e.g., below 1000 m) during spring is higher than that during summer, a result of the stronger new particle formation (NPF) events due to the reduced condensation sink in spring. In the BL, the size of the aerosols gradually increases with altitude due to condensational growth and cloud processing. However, the chemical composition of the aerosols remained similar, with organics and sulfates representing 59.8 ± 2.2 % and 22.7 ± 2.1 %, respectively, of the total mass in the BL. Through the vertical profiles of aerosol properties, we observed NPF events in the upper BL during 7 out of 38 research flights, where the newly formed particles continue to grow as they are mixed down to the surface. There is also an indication that deep convection brings aerosols from the free troposphere (FT) to the surface, where they grow to contribute to the cloud condensation nuclei (CCN). Overall, the vertical heterogeneity of aerosols over the SGP is influenced by aerosol dynamics (new particle formation, growth, and cloud processing) and transport processes (mixing in the BL, long-range transport, entrainment, and convective downward transport). Case studies showing the influence of these factors are discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Reconciling differences between large-eddy simulations and Doppler-lidar observations of continental shallow cumulus cloud-base vertical velocity

We investigate a significant model-observation difference found between cloud-base vertical velocity for continental shallow cumulus simulated using large-eddy simulations (LES) and observed by Doppler lidar measurements over the U.S. Southern Great Plains ARM Facility. The LES cloud-base vertical velocity is dominated by updrafts that are consistent with a general picture for convective clouds but is inconsistent with Doppler lidar observations that also show the presence of considerable downdrafts. The underestimation of simulated downdrafts is found to be a robust feature, being insensitive to various numerical, physical, or dynamical choices. We find that simulations can more closely reproduce observations only after improving the model physics to use size-resolved microphysics and horizontal longwave radiation, both of which modify the cloud buoyancy and velocity structure near cloud side edges. The results suggest that treatments that capture these structures are needed for the proper simulation and subsequent parameterization development of shallow cumulus vertical transport.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Evaluating Shallow Convection Parameterization Assumptions With a q t – w Quadrant Analysis

Abstract Uncertainties associated with the response of shallow clouds to global warming remain a great challenge for climate projection. Due to the small size of these clouds, parameterizations are required to represent them in both current‐ and next‐generation climate models. We present a quantitative evaluation of several important assumptions used in both mass‐flux and Assumed‐PDF Higher‐Order Closure parameterizations of shallow convection. We use large‐eddy simulations (LESs) of four different shallow convection regimes as benchmarks and apply a q t (total moisture)– w (vertical velocity) quadrant analysis technique to identify the “coherent structures” of moist and dry up/down‐drafts. The statistics of these coherent structures and the environment are then used to evaluate commonly used assumptions in mass‐flux parameterizations related to (a) the convective downdrafts and (b) the subplume variability of convective updrafts. For quantitative evaluation of the PDF closure used in AP‐HOCs, we perform offline calculations with the PDF closure used in the Cloud Layers Unified By Bi‐normals and the Simplified Higher‐Order Closure schemes by supplying the closure with statistical quantities directly calculated from the LESs. Then, the impact of parameterization assumptions embedded in the PDF closure in the same two categories is analyzed and understood through comparisons of the output from the closure with the statistics of the moist and dry up/down‐drafts from the LESs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

The Effect of Updraft Entrainment on Convective Cell Deepening in Realistic Large-Eddy Simulations

Entrainment of surrounding cooler and drier air into convective updrafts is one of the key processes that influence deep convection initiation and growth. Numerous studies have investigated the effect of entrainment on isolated convective cloud growth in idealized simulations, but the importance of this effect in realistic conditions with many interacting convective clouds remains uncertain. We examine the impact of entrainment on the depth reached by convective clouds in realistic large-eddy simulations (LES) over central Argentina during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign. Cloudy updrafts and their associated properties are assigned to convective cells tracked with radar reflectivity signatures. Several thousand convective cells are tracked over two high convective available potential energy (CAPE) and two low CAPE cases that support cells of varying depths and intensities. Entrainment is calculated explicitly as the fluxes of air into the outer surface of each cloudy updraft. Single-predictor logistic regression models are used to determine the relative importance of updraft, near-updraft, and preconvective initiation atmospheric conditions in predicting whether convective cells become deep. We then build a multiple-predictor regression model pairing important updraft and meteorological metrics with fractional entrainment rate. The probability of cells transitioning to deep convection is most sensitive to ambient 600-hPa relative humidity (42% of total metric contribution to cloud depth predictability), followed by low-level CAPE (28%), cloud-base updraft width (19%), and fractional entrainment (11%). Thus, the initial width of the updraft along with potential buoyancy and its dilution through the midtroposphere collectively determine whether deep convection will result from shallower clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

The Radiative Properties of Small Clouds: Multi-Scale Observations and Modeling

Warm, liquid clouds and their representation in climate models continue to represent one of the most significant unknowns in climate sensitivity and climate change. Our project combines ARM observations, LES modeling, and satellite imagery to characterize shallow clouds and the role of aerosol in modifying their radiative effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

The parametric sensitivity of CAM5's MJO

Abstract We systematically explore the ability of the Community Atmospheric Model version 5 (CAM5) to simulate the Madden‐Julian Oscillation (MJO), through an analysis of MJO metrics calculated from a 1100‐member perturbed parameter ensemble of 5 year simulations with observed sea surface temperatures. Parameters from the deep convection scheme make the greatest contribution to the variance in MJO simulation quality with a much smaller contribution from parameters in the large‐scale cloud, shallow convection, and boundary layer turbulence schemes. Improved MJO variability results from a larger lateral entrainment rate and a reduction in the precipitation efficiency of deep convection that was achieved by a smaller autoconversion of cloud to rainwater and a larger evaporation of convective precipitation. Unfortunately, simulations with an improved MJO also have a significant negative impact on the climatological values of low‐level cloud and absorbed shortwave radiation, suggesting that structural in addition to parametric modifications to CAM5's parameterization suite are needed in order to simultaneously well simulate the MJO and mean‐state climate.

Boyle, J. S.↗
DOE OSTI2017

Influence of Superparameterization and a Higher-Order Turbulence Closure on Rainfall Bias Over Amazonia in Community Atmosphere Model Version 5

In this work, we evaluate the Community Atmosphere Model Version 5 (CAM5) with a higher-order turbulence closure scheme, named Cloud Layers Unified By Binomials (CLUBB), and a Multiscale Modeling Framework (MMF) with two different microphysics configurations to investigate their influences on rainfall simulations over Southern Amazonia. The two different microphysics configurations in MMF are the one-moment cloud microphysics without aerosol treatment (SAM1MOM) and two-moment cloud microphysics coupled with aerosol treatment (SAM2MOM). Results show that both MMF-SAM2MOM and CLUBB effectively reduce the low biases of rainfall, mainly during the wet season. The CLUBB reduces low biases of humidity in the lower troposphere with further reduced shallow clouds. The latter enables more surface solar flux, leading to stronger convection and more rainfall. MMF, especially MMF-SAM2MOM, unstablizes the atmosphere with more moisture and higher atmospheric temperatures in the atmospheric boundary layer, allowing the growth of more extreme convection and further generating more deep convection. MMF-SAM2MOM significantly increases rainfall in the afternoon, but it does not reduce the early bias of the diurnal rainfall peak; LUBB, on the other hand, delays the afternoon peak time and produces more precipitation in the early morning, due to more realistic gradual transition between shallow and deep convection. MMF appears to be able to realistically capture the observed increase of relative humidity prior to deep convection, especially with its two-moment configuration. In contrast, in CAM5 and CAM5 with CLUBB, occurrence of deep convection in these models appears to be a result of stronger heating rather than higher relative humidity.

58 GEOSCIENCES↗
DOE OSTI2021

Determining Spatial Scales of Soil Moisture—Cloud Coupling Pathways Using Semi-Idealized Simulations

The spatial scales of land-atmosphere interactions over heterogeneous, realistic soil moisture patterns are critical to improve our understanding of land-atmosphere interactions. However, these scales are poorly quantified. We use high-resolution numerical experiments to quantify the spatial scales for a selected day during the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) campaign in Oklahoma. A semi-idealized approach (removing background winds and surface topography while retaining the real-world data for other boundary conditions) enables examination of the local influence from the surface. Simulations that apply uniform surface, variable land cover with uniform soil moisture, and variable land cover with variable soil moisture are then compared. Land cover variations, especially water and urban surfaces, create two variance peaks in the surface sensible heat flux in the scales >10 km (meso-β) and <6 km (meso-γ). Both peaks are enhanced by the observation-based soil moisture distribution that has most of its variance in the meso-β scale. Atmospheric response in the meso-β scale is hydrostatic with weak vertical motion. The land cover variations induce secondary circulations in the scales of 2.5–6 km. The additional soil moisture variability intensifies extreme circulations over dry soil patches and sharp sensible heat flux gradients, slightly extending the characteristic scales to 2.5–9 km. While their areal coverage is small, soil moisture variations on such “hotspots” lead to substantially larger convective cloud structure and domain-mean rainfall, calling for a consideration of their non-linear effect in large-scale models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Impact of Meteorological Factors on the Mesoscale Morphology of Cloud Streets during a Cold-Air Outbreak over the Western North Atlantic

We report postfrontal clouds (PFC) are ubiquitous in the marine boundary layer, and their morphology is essential to estimating the radiation budget in weather and climate models. Here we examine the roles of sea surface temperature (SST) and meteorological factors in controlling the mesoscale morphology and evolution of shallow clouds associated with a cold-air outbreak that occurred on 1 March 2020 during phase I of the Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE). Our results show that the simulated PFC structure and ambient conditions by the Weather Research and Forecasting (WRF) Model are generally consistent with observations from GOES-16 and dropsonde measurements. We also examine the thermodynamical and dynamical influences in the cloud mesoscale morphology using WRF sensitivity experiments driven by two meteorological forcing datasets with different domain-mean SST and spatial gradients, which lead to dissimilar values of hydrometeor water path and cloud core fraction. The SST from ERA5 leads to weaker stability and higher inversion height than the SST from FNL does. In addition, the use of large-scale meteorological forcings from ERA5 yields a distinctive time evolution of wind direction shear in the inner domain, which favors the formation and persistence of longer cloud rolls. Both factors contribute to a change in the time evolution of domain-mean water path and cloud core fraction of cloud streets. Our study takes advantage of the simulation driven by the differences between two large-scale forcing datasets to illustrate the importance of SST and wind direction shear in the cloud street morphology in a realistic scenario.

54 ENVIRONMENTAL SCIENCES↗